The load forecasting problem is a complex nonlinear problem linked with social considerations, economic factors, and weather variations. In particular, load forecasting for holidays is a challenging ...

5 Alternative methods Besides trimming and winsorizing, there are other methods to deal with outliers in regression, such as transforming the data, using robust estimators, or adding dummy variables.

A novel approach for the parameter estimation of polynomial phase signals (PPSs) is proposed. Unlike the existing methods, the proposed method uses the spectrum phase (SP) rather than the traditional ...

linear-regression image-processing logistic-regression feedforward-neural-network gradient-descent polynomial-regression data-normalization convolutional-neural-network softmax-regression ...

The Green Bay Packers made a major decision on Monday, releasing veteran cornerback Jaire Alexander—once a key piece of their defense when healthy. The move removes a potential distraction from ...

The project will be focused on using regression to predict the "charges" target values of an insurance dataset based on different features. To make this possible we are going to make four different ...